BalancedKMeansLearn Method

Learns a model that can map the given inputs to the desired outputs. Note: the model created by this function will not be able to produce balanced clusterings. To retrieve the balanced labels, check the Labels property of this class after calling this function.

Namespace: Accord.MachineLearning
Assembly: Accord.MachineLearning (in Accord.MachineLearning.dll) Version: 3.8.0

Syntax

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public override KMeansClusterCollection Learn(
	double[][] x,
	double[] weights = null
)

Public Overrides Function Learn ( 
	x As Double()(),
	Optional weights As Double() = Nothing
) As KMeansClusterCollection

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Parameters

x: Type: SystemDouble
The model inputs.
weights (Optional): Type: SystemDouble
The weight of importance for each input sample.

Return Value

Type: KMeansClusterCollection
A model that has learned how to produce suitable outputs given the input data x.

Implements

IUnsupervisedLearningTModel, TInput, TOutputLearn(TInput, Double)

Reference

BalancedKMeans Class

Accord.MachineLearning Namespace

BalancedKMeansAddLanguageSpecificTextSet("LST63A080C5_0?cpp=::|nu=.");Learn Method

Parameters

Return Value

Implements

Reference

BalancedKMeansLearn Method